Senior Data Engineering Manager - Capacity Engineering, Apple Services Engineering
Confirmed on the employer's own hiring board on Oct 19, 2026. First seen by Alion on Jul 29, 2026. Apple scores B on the Alion truth index.
At Apple, we believe that innovation flourishes in an environment where ideas are challenged, collaboration is encouraged, and technology is pushed to its limits. This environment is only possible when diverse minds come together, bringing unique perspectives and experiences. Our people and their ideas inspire innovation in everything we do. Imagine what you could accomplish here!
Apple Services Engineering (ASE) teams build and scale the platforms and infrastructure behind many of Apple's services - including iCloud, iTunes, Siri, and Maps. The Capacity Engineering team sits at the center of how Apple plans, buys, and operates the compute, storage, and data-services capacity those services run on. We are looking for a Senior Data Engineering Manager to lead the data engineering team that turns raw fleet, demand, and supply signals into the trusted data and insight that drive Apple's infrastructure and capacity-planning strategy.
This is a hands-on leadership role. You will own the data lake at the heart of capacity engineering - the single source of truth for supply, demand, utilization, and cost across Apple's cloud - and lead a talented, geographically distributed team that builds the ingestion pipelines, data models, and analytics that leadership relies on to make multi-hundred-million-dollar capacity decisions.
Description
Reporting into Capacity Engineering, you will lead a team of engineers responsible for the capacity data lake and the pipelines, services, and analyses built on top of it. Your team owns the data that connects customer demand, platform supply, hardware fulfillment, utilization, and cost - and makes it accurate, governed, and accessible to planners, finance, platform owners, and executives.
You will set the technical direction for how capacity data is ingested, modeled, governed, and served; hold a high bar on data quality and reliability; and partner closely with forecasting, reservation/quota, platform, and finance teams as well as our Engineering Program Management partners. You will be a visible technical contributor, going deep into architecture, data models, and thorny data-quality problems alongside the team, rather than directing from a distance.
This is a chance to build foundational capacity-data systems that are central to capacity availability - one of the most critical topics for Apple's infrastructure - where the impact of getting it right is immediate and organization-wide.
Minimum Qualifications
BS/MS in Computer Science, Engineering, or equivalent practical experience.
3+ years of engineering leadership experience, including hiring, mentoring, and growing engineers.
Strong, hands-on data engineering background - designing and operating data lakes, data models, and large-scale ingestion/ETL pipelines, with a track record of driving data quality, governance, and accessibility.
Experience with modern big-data and data-lake technologies such as Spark, Databricks, Hadoop, and cloud data stores (e.g., Aurora / S3-compatible storage).
Ability to remain technically hands-on - leading architecture reviews, modeling data, and going deep into technical detail.
Strong data-analysis instincts: able to derive and communicate business insight from complex, heterogeneous data.
Excellent written and verbal communication; able to present technical strategy and data-driven recommendations to both engineers and senior leadership.
Willingness and ability to be based in Seattle and to lead a geographically distributed team.
Preferred Qualifications
Experience managing across locations and time zones; experience managing managers is a plus.
Domain experience in cloud infrastructure and capacity planning - supply/demand, forecasting, utilization/efficiency, cost optimization, or fulfillment.
Familiarity with capacity and cost concepts across first-party and third-party cloud (CAPEX vs. OPEX vs. cloud spend), chargeback/showback, and attribution.
Experience building the data foundations for forecasting, planning, or FinOps-style cost/efficiency programs.
Experience introducing AI/LLM-assisted tooling into data engineering and analytics workflows.
Background in data governance, access control, or compliance-sensitive data environments.
A builder's mindset - comfortable establishing foundational systems and processes where they don't yet exist.